As we bid farewell to the transformative year of 2023, this blog reflects on the unparalleled strides in technology, spotlighting Generative AI, Large Language Models (LLMs), and the imperative role of data security and governance. The essence of AWS re:Invent 2023, crowned as the 'Year of Generative AI and LLMs,' resonates as a milestone event that celebrated groundbreaking innovations, notably the powerful generative AI assistant, Amazon Q. Beyond the technological marvels, the blog underscores the significance of data security and governance, setting the stage for a deep dive into key announcements and the transformative impact of TrustLogix in this dynamic landscape.
AWS re:Invent Recap
Our focus for this blog is the area of data analytics platforms, let's look at some of the key announcements at AWS re:Invent in this space:
- Redshift AWS Q Integration
- Multi-data warehouse writes through data sharing
- Generative BI Authoring capabilities in Amazon Quick Sight
- New Foundation Models in Bedrock
- Zero ETL Integrations
Redshift Integrations
The Redshift AWS Q integration provides a business advantage by simplifying query authoring and increasing productivity through natural language queries and AI-driven SQL code recommendations. Generative SQL analyzes user intent and schema metadata, allowing for swift insights in a conversational format and streamlining decision-making without requiring extensive knowledge of complex database metadata.
Quick Sight Integrations
Now business users have the ability to create compelling and shareable narratives to explore their data, access executive summaries of dashboards that rapidly surface key insights, and respond confidently to data inquiries not addressed by dashboards and reports, through an enhanced Q&A experience.
Zero ETL Integrations
AWS's zero-ETL is designed to alleviate the challenges associated with building and managing data pipelines. This enables customers to effortlessly connect all their data, regardless of its location. This includes data in Aurora PostgreSQL, Amazon DynamoDB, and Amazon RDS for MySQL zero-ETL integrations with Amazon Redshift making it easier to analyze transactional data without building and maintaining data pipelines.
Bedrock Innovations
Amazon Bedrock innovations expand model choice and deliver powerful capabilities, making it easier for customers to build and scale generative artificial intelligence (AI) applications customized to their businesses. Using Bedrock, customers can customize models with fine-tuning support for Cohere Command, Meta Llama 2, and Amazon Titan models, with Anthropic's Claude coming soon.
Each of these features contributes significantly, enabling customers to automate processes and expedite the transfer of data into the cloud. The ultimate goal is to furnish real-time business insights through streamlined operations.
The Role of the Data Security Team in this Transformation
Transitioning to the critical role of security teams in these rapid innovations, it becomes evident that as businesses embrace streamlined processes and innovative data analytics platforms, security cannot be overlooked. In this era of accelerated transformation, data security teams must equip themselves with powerful tools to guarantee the integrity and protection of sensitive information throughout these advanced procedures. AWS and other cloud platforms come with building blocks to secure, but one key question the security teams are left with is, “Is everything implemented as per our policies?” before they allow data people to move fast.
How TrustLogix Helps
Understanding the typical challenges and gaps in one's current data security posture is crucial for fast-moving data projects. Defining roles and access policies for specific data sources, and detecting issues encompassing "Dark Data," are common challenges. The presence of "Role Explosion" signifies a multitude of roles with overlapping privileges, leading to operational confusion. Another aspect involves identifying "ghost accounts" that have remained inactive for an extended period. Vigilance is required to monitor usage behavior for unusual patterns, such as spikes in data volumes or accessing data at unusual times, as well as unauthorized access from clients. The concept of "Data Sprawl" is also important, examining whether tables or schemas are being copied or transferred from a data store to various targets, potentially with disparate access controls compared to the source.
If you would like to know more about how TrustLogix is helping customers adopt Generative AI and LLMs in a secure and compliant way, please schedule a demo.
